Research

My research has always had a strong methodological focus and is characterized by the development, refinement, and application of advanced statistical methods across various areas of psychology.

Currently, my research projects focus on two main areas:

The first area is related to Clinical Neuropsychology, where I develop and refine neuropsychological tests to enhance diagnostic accuracy and clinical assessment. Over the years, I have developed more than ten neuropsychological tests, introducing innovative elements such as the use of Cognitive Reserve as a predictor to consider in the calculation of cut-off scores from normative data, and the development of regression methods for more accurate clinical cut-offs.

The second area is related to Cognitive Neuroscience, with a focus on the neuroscience of language and its clinical applications. In recent years, I have concentrated particularly on how viewing the brain as a predictive machine (an approach associated with predictive processing and the Bayesian brain) can provide new perspectives on cognitive disorders traditionally associated with classical constructs (such as attention, memory, executive functions, etc.). This is explored through studies involving patients or research utilizing various brain activity recording techniques, primarily neurophysiological.

Another key aspect of my research is the creation of code and software, which I make freely available on my personal web pages. I am a passionate advocate for Open Science, committed to promoting scientific rigor, transparency, and the open sharing of data and code to foster collaboration and innovation in my scientific fields.